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shreyaskal3
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speaker-segmentation-fine-tuned-hindi

Transformers
TensorBoard
Safetensors
Hindi
pyannet
speaker-diarization
speaker-segmentation
Generated from Trainer
Model card Files
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  1. README.md +73 -0
  2. model.safetensors +1 -1
  3. runs/Jan06_09-53-35_44c4e1bfef13/events.out.tfevents.1736157232.44c4e1bfef13.1365.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - hi
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+ license: mit
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+ base_model: pyannote/speaker-diarization-3.1
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+ tags:
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+ - speaker-diarization
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+ - speaker-segmentation
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+ - generated_from_trainer
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+ datasets:
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+ - Samyak29/synthetic-speaker-diarization-dataset-hindi-large
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+ model-index:
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+ - name: speaker-segmentation-fine-tuned-hindi
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # speaker-segmentation-fine-tuned-hindi
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+
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+ This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the Samyak29/synthetic-speaker-diarization-dataset-hindi-large dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3905
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+ - Model Preparation Time: 0.0039
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+ - Der: 0.1286
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+ - False Alarm: 0.0227
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+ - Missed Detection: 0.0270
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+ - Confusion: 0.0790
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
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+ | 0.4526 | 1.0 | 219 | 0.4401 | 0.0039 | 0.1423 | 0.0261 | 0.0297 | 0.0864 |
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+ | 0.4004 | 2.0 | 438 | 0.4090 | 0.0039 | 0.1334 | 0.0228 | 0.0297 | 0.0810 |
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+ | 0.3571 | 3.0 | 657 | 0.3891 | 0.0039 | 0.1249 | 0.0224 | 0.0273 | 0.0752 |
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+ | 0.3497 | 4.0 | 876 | 0.3877 | 0.0039 | 0.1269 | 0.0238 | 0.0264 | 0.0767 |
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+ | 0.3609 | 5.0 | 1095 | 0.3905 | 0.0039 | 0.1286 | 0.0227 | 0.0270 | 0.0790 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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